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Volume 13, Issue 4 (2025)
Health Educ Health Promot 2025, 13(4): 1001-1011 |
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Received: 2025/10/6 | Accepted: 2025/12/13 | Published: 2025/11/19
Received: 2025/10/6 | Accepted: 2025/12/13 | Published: 2025/11/19
How to cite this article
Esmaili dolabenezhad S, bahrambeygi F, besharati S. The use of artificial intelligence in nursing to accelerate the treatment process of patients with focus in Iran. Health Educ Health Promot 2025; 13 (4) :1001-1011
URL: http://hehp.modares.ac.ir/article-4-82927-en.html
URL: http://hehp.modares.ac.ir/article-4-82927-en.html
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Abstract (101 Views)
Aims: of this review article was synthesizes current literature on the application of AI in nursing practice and accelerate the treatment process of patients with focus in Iran.
Methods: The integration of artificial intelligence (AI) in healthcare represents a transformative shift in nursing practice and patient care delivery. This comprehensive review analyzed multiple studies conducted between 2023-2025 focusing on AI integration in Iranian nursing practice. We employed systematic literature search strategies across multiple databases including PubMed, CINAHL, and Google Scholar, using keywords related to AI, nursing, Iran, and patient treatment acceleration. Data from both qualitative and quantitative studies were synthesized to provide a comprehensive overview.
Result: Iranian nurses demonstrate moderate acceptance (74.6% at moderate level) and positive attitudes (65.8% good attitude) toward AI despite significant knowledge gaps (41.1% with low knowledge). AI applications in Iranian healthcare settings have shown promise in predictive analytics, clinical decision support systems, and administrative task automation. Significant positive correlations were found between nurses' knowledge and their attitude (R=0.311, p<0.001), application (R=0.514, p<0.001), and acceptance (R=0.381, p<0.001) of AI technologies.
Conclusion: AI technologies hold significant promise for accelerating treatment processes in Iranian healthcare settings through enhanced decision-making, predictive analytics, and workflow automation. Strategic investments in nursing education, infrastructure development, and policy frameworks are necessary to fully realize AI's potential in transforming nursing practice and improving patient care outcomes in Iran.
Methods: The integration of artificial intelligence (AI) in healthcare represents a transformative shift in nursing practice and patient care delivery. This comprehensive review analyzed multiple studies conducted between 2023-2025 focusing on AI integration in Iranian nursing practice. We employed systematic literature search strategies across multiple databases including PubMed, CINAHL, and Google Scholar, using keywords related to AI, nursing, Iran, and patient treatment acceleration. Data from both qualitative and quantitative studies were synthesized to provide a comprehensive overview.
Result: Iranian nurses demonstrate moderate acceptance (74.6% at moderate level) and positive attitudes (65.8% good attitude) toward AI despite significant knowledge gaps (41.1% with low knowledge). AI applications in Iranian healthcare settings have shown promise in predictive analytics, clinical decision support systems, and administrative task automation. Significant positive correlations were found between nurses' knowledge and their attitude (R=0.311, p<0.001), application (R=0.514, p<0.001), and acceptance (R=0.381, p<0.001) of AI technologies.
Conclusion: AI technologies hold significant promise for accelerating treatment processes in Iranian healthcare settings through enhanced decision-making, predictive analytics, and workflow automation. Strategic investments in nursing education, infrastructure development, and policy frameworks are necessary to fully realize AI's potential in transforming nursing practice and improving patient care outcomes in Iran.
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